Study Explores Possible Relationship Between Crime and 3am Bars

February 22, 2017

Researchers have known for a while that there is a positive relationship between alcohol availability and crime rates – that is, neighborhoods that have plentiful bars and liquor stores tend to have more crime than those that do not.

While this evidence is somewhat useful on its own, many details about this relationship remain unknown. Rosa Schulz, Master of Public Health (MPH) candidate at the Brown School at Washington University and practicum student at the Institute’s Public Health Data and Training Center, sought to explore this issue and how it was manifested in the City of St. Louis.

Background

In the state of Missouri, bars and restaurants that serve alcohol are required to close by 1:30 am. To stay open later, they must have a special license issued by their city or county. In the City of St. Louis, just over 100 bars have liquor licenses that allow them to stay open until 3am and most of these (57) are located in the Downtown or Downtown West neighborhoods.

The main question, is there a difference in crime rate around bars with 3am liquor licenses? Conversations between the City and the Data Center led to an exploratory study, and Schulz agreed to devote her data analysis, data visualization (data viz), and geographic information system (GIS) mapping skills to investigate.

“I’m interested in how we can use maps to tell stories, and how we can use multiple data sources to make data viz more powerful,” Schulz explained.

Schulz obtained a list of bars with 3am licenses from the City of St. Louis, a database of crimes that occurred from the police department, and data from the United States Census Bureau and went to work. Her three research questions were:

Is there spatial clustering of crimes around 3am bars that is higher than would be expected by chance?

Does crime increase proportionally as the distance from a 3am bar increases?

How might factors such as neighborhood demographics and distance from crime to nearest 3am bar contribute to this analysis?

She specifically investigated firearm and “person crimes” – crimes like armed robbery, assault, and rape. (Homicides were not included in the analysis).

Findings

GIS maps from 3am bar and crime study (click to see in motion)

An optimized hot spot analysis of crime indicated that neighborhoods near the eastern edge of the city (in and around Downtown) did show more spatial clustering of crimes around 3am bars than would be expected by chance. Neighborhoods in the southwestern area of the city, however, show less clustering than would be expected.

A concentric buffer analysis allowed Schulz to see if the number of crimes committed were highest nearest 3am bars, and decreased as one moved farther away. She found that person crimes decreased as the distance from each 3am bar increased, although the same was not true for firearm crimes.

Overall, Schulz found mixed evidence on whether or not the preponderance of 3am bars can explain the number of person crimes that occur in the City of St. Louis by location. The two neighborhoods that had the highest number of 3am bars (Downtown and Downtown West) did indeed have the highest levels of person crime between midnight and 6am. However, the remaining three neighborhoods with the highest levels of person crimes had very few 3am bars (Dutchtown, Jeff-Vander-Lou, and Wells Goodfellow).

Downtown St. Louis is a populous area with a high volume of tourists at certain times. The connection between high crime volume and 3am bars in the area could simply be a result of an increased population (more perpetrators and more victims). Further research should take into account the temporary population fluctuations around downtown events and attractions. It is clear that more analysis is needed to uncover the full list of factors driving crimes in St. Louis.

What’s next for Rosa?

Schulz will graduate from the Brown School in May, and hopes to continue finding ways to use GIS to improve public health.

For more information on this study, its methods or findings, contact Rosa Schulz at rosaschulz@wustl.edu.